Bayesian Inference for Analyzing Sports Data by Using Bivariate Poisson models
Abstract
Bivariate distribution models are commonly used to analyze sports data and data from various fields. These models are used to analyze discrete count data with two dependent variables in the data. In this research article, we have used Bivariate Poisson and Diagonally Inflated Bivariate Poisson regression models. We have proposed an estimation procedure in the Bayesian framework in conjunction with the augmentation of data. For parameter estimation, we use Gaussian priors and beta priors for both models. To illustrate the fitting performances of our suggested models we have performed real data analysis on English Premier League soccer data.
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